Classification is a data mining (DM) technique used to predict or forecast the unknown information using the historical data. There are many classification techniques. ID3 is a very popular tree based classification algorithm for a categorical data which does not support continuous data. Attribute selection process plays major role in building a classification tree model. Attribute Selection in...

Humans focus attention on different face regions when recognizing face attributes. Most existing face attribute classification methods use the whole image as input. Moreover, some of these methods rely on fiducial landmarks to provide defined face parts. In this paper, we propose a cascade network that simultaneously learns to localize face regions specific to attributes and performs attribute ...

Attribute reduction is one of the core issues of the rough set theory. The traditional method of attribute reduction was designed based on positive region unchanged, as abandoning processing the incompatible data in the boundary domain, so the classification characteristics of the reduction results are not necessarily best. In this paper, the concept of relative approximate degree is proposed i...

It has been demonstrated that the speech recognition performance can be improved by adding extra articulatory information, and subsequently, how to use such information effectively becomes a challenging problem. In this paper, we propose an attribute-based knowledge integration architecture which is realized by modeling and learning both acoustic and articulatory cues simultaneously in a unifor...

While traditional approaches in object recognition require the specification of training examples from each class and the application of class specific classifiers, in real world situations, the immensity of the number of image classes makes this task daunting. A novel approach in object recognition is attribute based classification, where instead of training classifiers for the recognition of ...